Please use this identifier to cite or link to this item:
Title: Modeling the recipe composition of food products and recommendations for their use in individual nutrition
Authors: Sadovoy, V. V.
Садовой, В. В.
Shchedrina, T. V.
Щедрина, Т. В.
Keywords: Biotechnology;Sustainable development;Complex networks;Data mining;Proteins;Food products;Environmental management;Nutrition
Issue Date: 2020
Publisher: IOP Publishing Ltd
Citation: Sadovoy, V.V., Voblikova, T.V., Permyakov, A.V., Shchedrina, T.V., Morgunova, A.V., Stolyarova, V.V. Modeling the recipe composition of food products and recommendations for their use in individual nutrition // IOP Conference Series: Earth and Environmental Science. - 2020. - Volume 613. - Issue 1. - Номер статьи 012127
Series/Report no.: IOP Conference Series: Earth and Environmental Science
Abstract: To determine the body type of an individual according to the input parameters (age, gender, height and weight), a model is developed based on the statistical module classification trees. Based on the analysis of body type, labor intensity, gender, weight and nutritional structure for various categories of citizens, a neural network design of an algorithm for calculating the daily intake of protein, fat, dietary fiber and energy is carried out. The obtained data can serve as the basis for drawing up an individual nutritional diet. Taking into account the amino acid composition, organoleptic and economic indicators, a database is developed that allows to determine the optimal recipe of a meat product for individual nutrition. A structural-parametric model consisting of three stages (establishing the body type; determination of calorie content and requirements for protein and fat of animal origin; calculation of the energy value of the daily diet) is created in the Data Mining module to desing a products composition for individual nutrition
Appears in Collections:Статьи, проиндексированные в SCOPUS, WOS

Files in This Item:
File Description SizeFormat 
scopusresults 1562 .pdf
  Restricted Access
891.45 kBAdobe PDFView/Open
WoS 1132 .pdf
  Restricted Access
141.2 kBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.